Computer production of images from magnetic resonance has become an invaluable tool in medicine as the structural and biochemical information that can be obtained is helpful in the diagnosis of abnormalities without the possibly harmful effects of x-rays or gamma rays. Magnetic Resonance Imaging (MRI) provides better contrast between normal and diseased tissue than those produced by other computer-assisted imagery.
The final image product of an MRI must first go through a process of segmentation, which refers to the partitioning of a digital image into multiple segments in order to provide an image that is more meaningful or easier to analyze. Objects and boundaries in the image, such as lines, curves, and others, are located and enhanced using shared pixel characteristics, such as color, intensity, or texture. Bones, cartilage, ligaments, and other soft tissues of the body thus become identifiable by the trained eye.
While there exists many different techniques for segmenting MRI images, the quality of the output is only as good as the processing methods. There is therefore a need to improve on existing processing methods in order to provide a better output.